What Is Structured Query Language (SQL)?

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Structured Query Language, or SQL, is a programming nomenclature used to do set operations (like union, intersect, and minus) to organize and retrieve information in relational databases, based on “set theory and relational algebra.” According to DAMA International’s Data Management Body of Knowledge, in any system that uses SQL, “data elements or attributes, categorized into columns, are related into tuples (rows). Sets of relations with identical structure form tables.” These elements, correlated rows, columns, and tables form the basis for a Relational Database Management System (RDBMS).

SQL’s power comes from its conformity. According to the American National Standards Institute (ANSI), SQL is a data sub-language widely used to access relational databases. This means knowing and using SQL from RDBMS will be able to generalize to another RDBMS, resulting in efficient querying and reporting. Also, SQL can be picked up easily through accessible training and resources.

Other Definitions Include:

  • A “relational data language that provides a consistent, English keyword-oriented set of facilities for query, data definition, data manipulation, and data control.” (Gartner)
  • “The standard language for RDBMS for the last 40 years.” (Beth Narrish and Dan Hilton)
  • “A standard interface for RDBMS.” (Andrew Pavlo and Matthew Aslett)
  • “Language used to manage and administer the database server.” (Database Journal)
  • “Most common language for querying and manipulating data.” (Angela Zhang, Forbes)
  • “A query language designed for organizing, managing, developing and querying large relational databases over computer networks.” (IBM)
  • “A specialized language for updating, deleting and requesting information from databases.” (Indiana University)

Businesses Use SQL to:

  • Access and manipulate information
  • Generate reports to aid decision-making process
  • Make it easier to import and export data to/from different systems
  • To facilitate finding and supporting roles using data analysis
  • Provide strict ACID constraints to data assets

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